Results in hand tell us that letter identification is mediated by features (Pelli, Burns, Farell, and Moore, 1996). The features are bandlimited, with the same tuning as a spatial-frequency channel (Solomon and Pelli, 1994), and they are simple (Pelli, et al., 1966). This is consistent with the popular idea that features are like oriented center-surround receptive fields, or wavelets. We propose to: to use critical band masking in space and spatial frequency to identify the features that mediate visual detection and identification to use the candidate features to model letter identification performance with artificial and traditional alphabets. One reason for confidence in the success of this approach is that we have already succeeded in modeling word identification performance, taking letters as candidate features, showing that human performance approaches but never exceeds the performance of an otherwise-ideal observer that must base its decisions on independent latter identifications. Taking features to be smaller than a letter will bring the upper bound still lower making an even more stringent test. Exceeding that bound would disprove the conjecture that human performance is mediated by independent decisions on that set of features. Three other projects will use letters and noise to: characterize the channel mediating the poor acuity in amblyopic and normal fovea and periphery; (Pilot data indicate that our last-channel hypothesis may explain letter acuity.) measure equivalent noise in the periphery and compare it with predictions based on physiological measurements of ganglion cell noise; make fMRI measurements of contrast response paralleling our measure of efficiency of letter identification.